The 1400 mile southern border of the United States has historically been difficult to secure due to the vast stretches of land and the inhospitable nature of the terrain. This situation has resulted in a breach of our immigration laws but more importantly provides an opportunity for terrorists to illegally enter the country unobserved. Our phase I effort will demonstrate the feasibility of the signal processing for border security. Our system level approach relies on fusion of data from multiple sources to provide high probability detection and low probability false alarms across the diversity of terrain and intruder tracking over large distances. A combination of unattended ground sensors and pole mounted EO/IR sensors are used for initial intrusion detection. A highly automated UAV is used to provide tracking until the border patrol can apprehend the intruders. Three tiers of signal processing are used to achieve very high probability of detection (>98%) and low false alarm rates less than 3 per day. The three tiers are: pre-screening, object detection and classification, and evidence accumulation. During Phase I the performance of the signal processing algorithms will be measured using data collected at fouir sites along the border.